A global review and meta-analysis of applications of the freshwater Fish Invasiveness Screening Kit
Bibliographic record
Abstract
The freshwater Fish Invasiveness Screening Kit (FISK) has been applied in 35 risk assessment areas in 45 countries across the six inhabited continents (11 applications using FISK v1; 25 using FISK v2). The present study aimed: to assess the breadth of FISK applications and the confidence (certainty) levels associated with the decision-support tool’s 49 questions and its ability to distinguish between taxa of low-to-medium and high risk of becoming invasive, and thus provide climate-specific, generalised, calibrated thresholds for risk level categorisation; and to identify the most potentially invasive freshwater fish species on a global level. The 1973 risk assessments were carried out by 70 + experts on 372 taxa (47 of the 51 species listed as invasive in the Global Invasive Species Database www.iucngisd.org/gisd/ ), which in decreasing order of importance belonged to the taxonomic Orders Cypriniformes, Perciformes, Siluriformes, Characiformes, Salmoniformes, Cyprinodontiformes, with the remaining ≈ 8% of taxa distributed across an additional 13 orders. The most widely-screened species (in decreasing importance) were: grass carp Ctenopharyngodon idella, common carp Cyprinus carpio, rainbow trout Oncorhynchus mykiss, silver carp Hypophthalmichthys molitrix and topmouth gudgeon Pseudorasbora parva. Nine ‘globally’ high risk species were identified: common carp, black bullhead Ameiurus melas, round goby Neogobius melanostomus, Chinese (Amur) sleeper Perccottus glenii, brown bullhead Ameiurus nebulosus, eastern mosquitofish Gambusia holbrooki, largemouth (black) bass Micropterus salmoides, pumpkinseed Lepomis gibbosus and pikeperch Sander lucioperca. The relevance of this global review to policy, legislation, and risk assessment and management procedures is discussed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".